Exchange-Direct Financial Screening & Indian Capital Markets Architecture

### Exchange-Direct Data Architecture for Financial Screening Modern algorithmic and fundamental equity screening has historically depended on commercial middle-layer data vendors that scrape, aggregate, and normalize regulatory announcements. The introduction of exchange-native utilities like NSE Market Lens introduces structural improvements to data fidelity. 1. **Eliminating Scraper Latency and Reconciliation Drift**: - Commercial aggregators suffer from reconciliation lag (typically 2 to 24 hours) as scrapers re-parse PDF and XBRL filings. - Hosting screening engines directly on exchange infrastructure enables real-time ratio updates the moment audited quarterly results are validated through regulatory portals like NEAPS. 2. **Columnar In-Memory Ratio Computation**: - Querying across 2,400+ listed equities with multi-parameter bounds (such as P/E < 20, ROE > 18%, D/E < 0.3) requires high-throughput columnar storage. - Vectorized filtering delivers sub-50 millisecond response times without requiring distributed indexing tiers. 3. **Democratizing Institutional Data for Retail Participants**: - The growth of India's retail investor base (surpassing 104 million demat accounts) requires transparent, ad-free, and un-manipulated equity research tools to promote fact-based portfolio management over speculative social media tips.